About the job
Join a team at the forefront of defending Apple's ecosystem. We build the large-scale machine learning systems that protect millions of users from emerging threats and ensure the integrity of our products.
Responsibilities
Design, build, and deploy production-grade ML models to detect and mitigate abuse across multiple modalities (text, image, audio).
Own the full ML lifecycle: from prototyping and data analysis to deployment, monitoring, and the continuous improvement of models in production.
Drive the data strategy to continuously improve model performance by analyzing distribution gaps, contributing to synthetic data pipelines, and creating automated annotation systems.
Architect end-to-end systems for monitoring platform activity, detecting misuse, and triggering automated enforcement actions in real-time.
Collaborate with cross-functional partners in engineering, research, and product to define project requirements, establish technical direction, and deliver robust security solutions.
Qualifications
Minimum
2+ years experience shipping machine learning models to production. You have owned the end-to-end lifecycle of a model, from development to deployment and maintenance.
Strong familiarity with research fundamentals, machine learning principles, and development methodologies around LLMs, foundation models, and diffusion models
Proficient programming skills in Python and deep learning toolkits (e.g. JAX, PyTorch, Tensorflow)
Ability to work with sensitive and offensive content as part of building robust security and abuse detection systems.
Preferred
BS, MS or PhD in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Hands-on experience with fine-tuning or aligning large language models for security or safety applications.
Experience building large-scale data processing pipelines and ML infrastructure.
Experience driving technical projects and collaborating with large, diverse, cross-functional teams.